Zihao Li | Digital Economy | Best Researcher Award

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Prof. Zihao Li | Digital Economy | Best Researcher Award

 

Profile

Education

He obtained his PhD in Applied Economics from Hunan University, where he studied from September 2010 to June 2014. Prior to that, he completed his master’s degree in International Trade at Jiangnan University between September 2006 and July 2008. His academic journey began at Henan Normal University, where he earned his undergraduate degree in Economics from September 2002 to July 2006.

Work experience

Since September 2022, he has been serving as an Associate Professor, Professor, and Master Supervisor at the Business School of Nanjing University of Information Science and Technology. Prior to this, from June 2014 to August 2022, he worked at the International Business School of Henan University of Economics and Law as a Lecturer, Associate Professor, and Master Supervisor.

 

Achievement

He has authored several influential books, including Research on the Impact of Foreign Direct Investment on China’s Carbon Emissions (Economic Science Press, 2016), Foreign Direct Investment, Economic and Social Transformation and Environmental Pollution (China Financial and Economic Publishing House, 2017), and Economic and Social Transformation and Improvement of Local Government’s Environmental Governance (China Economic Publishing House, 2020).

His academic contributions have been recognized with multiple awards. He received the Third Prize of the Henan Social Science Outstanding Achievement Award (Provincial and Ministerial Level) in 2020 for his research on Environmental Governance of Local Governments with Spatial Relevance and Threshold Effect from the perspective of integrity. In 2019, he was awarded another Third Prize for his study on Local Government Tax Competition, Industrial Restructuring, and China’s Regional Green Development. Additionally, in 2016, his work on China’s Opening Up, Economic Transformation, and Low Carbon Economic Development earned him the Third Prize of the Hunan Provincial Social Science Outstanding Achievement Award.

Scientific Research Project

He has led several research projects funded by national and provincial institutions. Currently, he is hosting a General Program of the National Philosophy and Social Science Foundation (21BJY114), focusing on the Mechanism, Effect, and Policy of Digital Economy Promoting China’s Collaborative Governance of Carbon Smog (2021/9ā€“2024/9).

Previously, he successfully completed a Youth Program of the National Philosophy and Social Science Foundation (15CGL042), which examined Anti-Corruption and Environmental Governance Improvement of Local Governments (2015/6ā€“2019/12). He also led two provincial-level Soft Science Projects funded by the Henan Provincial Department of Science and Technology: one on Industrial Transfer and Green Development of Henan’s Industry (162400410201, 2016/6ā€“2017/9) and another on Enterprise Green Technology Innovation and Haze Pollution Control in Henan (202400410061, 2020/1ā€“2021/6).

 

Publication

  • (1) Zihao Li, Yue Wang, Tingting Bai. International digital trade and synergetic control of pollution and carbon emissions: Theory and evidence based on a nonlinear framework[J]. Journal of Environmental Management,2025, 376(3):124450.ļ¼ˆSCI, JCR Q1ļ¼‰

    (2) Zihao Li, Bingbing Yuan, Yue Wang, Jingwen Qian, Haitao Wu. The role of digital finance on the synergistic governance of pollution & carbon: Evidence from Chinese cities[J]. Sustainable Cities and Society,2024, 115(1):105812.ļ¼ˆSCI, JCR Q1ļ¼‰

    (3)ęŽå­č±Ŗ,ēŽ‹ę‚¦.ę•°å­—č“øꘓåƹ城åø‚å‡ę±”降ē¢³ååŒå‘展ēš„影响ā€”ā€”åŸŗäŗŽäŗ§äøšé›†čšäøŽč¦ē“ é…ē½®č§†č§’[J].ē»ęµŽē»ēŗ¬,2025,(1):67-79. (CSSCIę£€ē“¢)ļ¼›

    Zihao Li, Yue Wang. The impact of digital trade on the coordinated development of urban pollution reduction and carbon reduction: based on the perspective of industrial agglomeration and factor allocation[J] Economic longitude and latitude, 2025, (1):67-79. (CSSCI)

    (4) Zihao Li, Bai Tingting, Wang Yue, Wu Haitao. The Impact of Digital Government on Corporate Green Innovation: Evidence from China[J]. Technological Forecasting and Social Changeļ¼ˆSSCI, JCR Q1ļ¼‰

    (5) Tingting Bai, Yong Qi, Zihao Li, Dong Xu. Digital economy, industrial transformation and upgrading, and spatial transfer of carbon emissions: The paths for low-carbon transformation of Chinese cities[J]. Journal of Environmental Management, 2023, 344: 118528. (SCI, JCR Q1ļ¼ŒESI );

    (6) Bai Tingting, Qi Yong, Li Zihao*, Xu Dong. Will carbon emission trading policy improve the synergistic reduction efficiency of pollution and carbon? Evidence from216 Chinese cities[J]. Managerial and Decision Economics,2023,(8):1-24. (SSCI, JCR Q1, corresponding author)ļ¼›

    (7) Zihao Li, Bingbing Yuan, Tingting Bai, Dong Xu, Haitao Wu. Shooting two hawks with one arrow: The role of digitization on the coordinated development of resources and environment [J].ā€Æ Resources Policy, 2024, 90(3):104827. (SSCI, JCR Q1)

    (8) Zihao Li, Xihang Xie, Xinyue Yan, Tingting Bai, Dong Xu*. Impact of Chinaā€™s Rural Land Marketization on Ecological Environment Quality Based on Remote Sensing[J]. Int. J. Environ. Res. Public Health 2022, 19, 12619

    (SSCI, JCR Q1)

    (9) Zihao Li, Bai Tingting*, Tang Chang. How does the low-carbon city pilot policy affect the synergistic governance efficiency of carbon and smog? Quasi-experimental evidence from China[J]. Journal of Cleaner Production,2022(8): 133809 (SCI, JCR Q1)

    (10)ęŽå­č±Ŗ,čµµå…ƒ,å¤å­č°¦.ēŽÆäæē£ę”æäøŽåœ°ę–¹ę”æåŗœē¢³éœ¾ååŒę²»ē†ē»©ę•ˆęå‡ā€”ā€”åŸŗäŗŽēŽÆäæēŗ¦č°ˆēš„准č‡Ŗē„¶å®žéŖŒä¼°č®”[J].äø­å›½č½Æē§‘å­¦, 2023,(12):192-201. (CSSCIę£€ē“¢);

    Zihao Li, Yuan Zhao, Ziqian Xia. Performance improvement of coordinated governance of environmental protection supervision and local government carbon haze: quasi natural experimental estimation based on environmental interviews[J]. China Soft Science, 2023, (12): 192-201. (CSSCI)

    (11)ęŽå­č±Ŗ,ēŽ‹å€©å€©.ę•°å­—ē»ęµŽå‘å±•čƒ½å¦ę”¹å–„åœ°åŒŗé“¶č”Œäøšé£Žé™©ļ¼Ÿ-åŸŗäŗŽåŸŽåø‚商äøšé“¶č”Œēš„č€ƒåƟ[J].č“¢ē»č®ŗäø›,2023,(12):47-57.ļ¼ˆCSSCIļ¼‰ļ¼›

    Zihao Li, Qianqian Wang. Can the development of digital economy improve regional banking risks- Based on the Investigation of Urban Commercial Banks [J]. Collected Essays on Finance and Economics, 2023,(12):47-57.ļ¼ˆCSSCIļ¼‰

    (12)ęŽå­č±Ŗ,ē™½å©·å©·.ę”æåŗœēŽÆäæę”Æå‡ŗ态ē»æč‰²ęŠ€ęœÆåˆ›ę–°äøŽé›¾éœ¾ę±”ꟓ[J].ē§‘ē ”ē®”ē†,2021,(2):52-63. (CSSCIę£€ē“¢, 国家č‡Ŗē§‘åŸŗ金委ē®”ē†ē±»Aēŗ§é‡č¦ęœŸåˆŠļ¼Œć€Šę–°åŽę–‡ę‘˜ć€‹å…Øę–‡č½¬č½½)ļ¼›

    Zihao Li, Bai Tingting. Government environmental protection expenditure, green technology innovation and smog pollution[J]. Science Research Management, 2021, (2):52-63. (CSSCI)

    (13)ęŽå­č±Ŗ,č¢äø™å…µ.åœ°ę–¹ę”æåŗœēš„é›¾éœ¾ę²»ē†ę”æē­–作ē”Øęœŗ制: ę”æē­–å·„å…·ć€ē©ŗé—“å…³č”å’Œé—Ø꧛ꕈåŗ”[J].资ęŗē§‘å­¦ļ¼Œ 2021,(1):40-56. (CSSCIę£€ē“¢)ļ¼›

    Zihao Li, Bingbing Yuan. Local government’s policy mechanism for haze control: policy tools, spatial correlation and threshold effect [J]. Resource science, 2021,(1):40-56. (CSSCI);

    (14)ęŽå­č±Ŗ,č¢äø™å…µ.ē©ŗé—“å…³č”å’Œé—Ø꧛ꕈåŗ”ēš„åœ°ę–¹ę”æåŗœēŽÆå¢ƒę²»ē†ē ”ē©¶-åŸŗäŗŽå»‰ę“åŗ¦č§†č§’ēš„č€ƒåƟ[J].äø­å›½č½Æē§‘å­¦, 2019,(10):61-69. (CSSCIę£€ē“¢,国家č‡Ŗē§‘åŸŗ金委ē®”ē†ē±»Aēŗ§é‡č¦ęœŸåˆŠ)ļ¼›

    Zihao Li, Bingbing Yuan. A Study on Environmental Governance of Local Government Based on Spatial Correlation and Threshold Effect: An Investigation from the Perspective of Integrity. [J]. China Soft Science, 2019, (10):61-69. (CSSCI)

    (15) Zihao Li, Mao Jun. Local Governmentsā€™ Tax Competition, Industrial Structure Adjustment and Regional Green Development in China[J]. China Finance and Economic Review,2019(1): 93-111. (ESCI)ļ¼›

Dingming Wu | Computer Science | Best Researcher Award

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Dr. Dingming Wu | Computer Science | Best Researcher Award

 

Profile

  • scopus

Education

He holds a Ph.D. in Computer Science and Technology from Harbin Institute of Technology, where he studied under the supervision of Professor Xiaolong Wang from March 2018 to December 2022. Prior to that, he earned a Masterā€™s degree in Probability Theory and Mathematical Statistics from Shandong University of Science and Technology in collaboration with the University of Chinese Academy of Sciences, completing his studies under the guidance of Professor Tiande Guo between September 2014 and July 2017. His academic journey began with a Bachelorā€™s degree in Information and Computational Science from Shandong University of Science and Technology, which he completed between September 2006 and July 2010.

Work experience

He is currently a Postdoctoral Fellow at the University of Electronic Science and Technology of China, Chengdu, a position he has held since December 2022 and will continue until December 2024. His research focuses on EEG signal processing and algorithm feature extraction, specifically addressing the challenges posed by the complexity and individual variations of EEG signals. Given the limitations of traditional classification methods, his work aims to enhance recognition accuracy through advanced deep learning models, improving the decoding of intricate EEG signals and optimizing control accuracy. Additionally, he integrates artificial intelligence technologies to predict user intentions and provide proactive responses, ultimately enhancing the interactive experience. His system is designed for long-term stability and adaptability, leveraging self-learning mechanisms based on user feedback.

Previously, he worked as a Data Analyst at Qingdao Sanlujiu International Trade Co., Ltd., Shanghai, from September 2010 to July 2014. In this role, he was responsible for conducting statistical analysis of trade flow data.

Publication

  • [1] Dingming Wu, Xiaolong Wangāˆ—, and Shaocong Wu. Jointly modeling transfer learning of
    industrial chain information and deep learning for stock prediction[J]. Expert Systems with
    Applications, 2022, 191(7):116257.
    [2] Dingming Wu, Xiaolong Wangāˆ—, and Shaocong Wu.A hybrid framework based on extreme
    learning machine, discrete wavelet transform, and autoencoder with feature penalty for stock
    prediction[J]. Expert Systems with Applications, 2022, 207(24):118006.
    [3] Dingming Wu, Xiaolong Wangāˆ—, and Shaocong Wu. Construction of stock portfolio based on
    k-means clustering of continuous trend features[J]. Knowledge-Based Systems, 2022,
    252(18):109358.
    [4] Dingming Wu, Xiaolong Wangāˆ—, Jingyong Su, Buzhou Tang, and Shaocong Wu. A labeling
    method for financial time series prediction based on trends[J]. Entropy, 2020, 22(10):1162.
    [5] Dingming Wu, Xiaolong Wangāˆ—, and Shaocong Wu. A hybrid method based on extreme
    learning machine and wavelet transform denoising for stock prediction[J]. Entropy, 2021,
    23(4):440.
    Papers to be published:
    [6] Wavelet transform in conjunction with temporal convolutional networks for time series
    prediction. Journal: PATTERN RECOGNITION; Status: under review; Position: Sole
    Author.
    [7] A Multidimensional Adaptive Transformer Network for Fatigue Detection. Journal: Cognitive
    Neurodynamics; Status: accept; Position: First Author.
    [8] A Multi-branch Feature Fusion Deep Learning Model for EEG-Based Cross-Subject Motor
    Imagery Classification. Journal: ENGINEERING APPLICATIONS OF ARTIFICIAL
    INTELLIGENCE; Status: under review; Position: First Author.
    [9] A Coupling of Common-Private Topological Patterns Learning Approach for Mitigating Interindividual Variability in EEG-based Emotion Recognition. Journal: Biomedical Signal
    Processing and Control; Status: Revise; Position: First Corresponding Author.
    [10] A Function-Structure Adaptive Decoupled Learning Framework for Multi-Cognitive Tasks
    EEG Decoding. Journal: IEEE Transactions on Neural Networks and Learning Systems;
    Status: under review; Position: Co-First Author.
    [11] Decoding Topology-Implicit EEG Representations Under Manifold-Euclidean Hybrid Space.
    Computer conference: International Joint Conference on Artificial Intelligence 2025 (IJCAI);
    Status: under review; Position: Second Corresponding Author.
    [12] Style Transfer Mapping for EEG-Based Neuropsychiatric Diseases Recognition. Journal:
    EXPERT SYSTEMS WITH APPLICATIONS; Status: under review; Position: Second
    Corresponding Author.
    [13] An Adaptive Ascending Learning Strategy Based on Graph Optional Interaction for EEG
    Decoding. Computer conference: International Joint Conference on Artificial Intelligence
    2025 (IJCAI); Status: under review; Position: Second Corresponding Author.
    [14] A Transfer Optimization Methodology of Graph Representation Incorporating CommonPrivate Feature Decomposition for EEG Emotion Recognition. Computer conference:
    International Joint Conference on Artificial Intelligence 2025 (IJCAI); Status: under review;
    Position: Second Corresponding Author.
    [15] An Interpretable Neural Network Incorporating Rule-Based Constraints for EEG Emotion
    Recognition. Computer conference: International Joint Conference on Artificial Intelligence
    2025 (IJCAI); Status: under review; Position: First Author.